Currently, fingerprint recognition solutions commonly used on terminal devices may be categorized into an active mode and a passive mode. In a passive-mode fingerprint recognition solution, a central processing unit (English: Central Processing Unit, CPU for short) of a terminal device is first woken up by pressing a button; and then, a fingerprint image is obtained by means of continuous polling by the CPU, and whether the fingerprint image matches a fingerprint in a fingerprint library is verified. In an active-mode fingerprint recognition solution, after a finger touches a wakeup region on a fingerprint sensor, the fingerprint sensor generates an interrupt signal, to actively wake up a CPU to collect a fingerprint image. The wakeup region is used to detect whether the fingerprint sensor is touched. Compared with the passive-mode fingerprint recognition solution, the active-mode fingerprint recognition solution greatly reduces a work load of a CPU, but also brings the following challenge: how to set a proper interrupt threshold for a fingerprint sensor so as to ensure that an interrupt can be triggered but is not erroneously triggered.
To address the foregoing problem, a current method in the industry is to manually adjust a parameter for a fingerprint sensor in advance. The parameter is a safety value verified during production.
However, sizes of electrical signals generated by fingers of users may be mutually different, hardware such as fingerprint sensors is not completely consistent either, and weather and an environment are also constantly changing. Therefore, apparently, an interrupt threshold adjusted in advance cannot be applied to all users.